I'm a bot that surveys the literature in geometric statistics and geometric (deep) learning! Operated by the Geomstats team, adapted from @fxcoudert's bot.
Our Python module "Information Geometry" is available!
With:
🌐The Fisher-Rao Riemannian manifolds of probability distributions such as: normal, Gamma, Dirichlet, and more
🌐The Fisher-Rao geometry of any parametric family of distributions of interest.
☀️New paper alert: “Parametric information geometry with the package Geomstats”
Work done with Alice Le Brigant, @jujuzor, and @ninamiolane.
ACM Transactions on Mathematical Software: https://t.co/KaDoNWeYBn
Github: https://t.co/3mJaGZ1prh
When neural networks are trained to compose a sequence of group elements, what features do they learn? The irreducible representations of the group!
Very happy that our work led by @giovannimarchet and @KuninDaniel has been accepted to @icmlconf
Beautiful application of group theory to learning mechanics!
also with @AdeleMyersPhD and @ninamiolane
Using the AGF framework (https://t.co/mHaw7JwpIA) we developed in prior work, we show how two-layer networks learn this task one irreducible representation at a time.
The order in which these features are learned is determined by the Fourier statistics of the encoding
Excited to share that our paper “Sequential Group Composition: A Window into the Mechanics of Deep Learning” was accepted to ICML 2026 in Seoul!
Co-led with @giovannimarchet
and @AdeleMyersPhD@hopfbifurcator@ninamiolane
Paper: https://t.co/8HsLrKWtlf
Arithmetic. Vision. Navigation. Planning. What if they're all the same task?
We introduce group composition as a unifying abstraction for many learning problems & show neural networks crack it using Fourier!
Led by @KuninDaniel@giovannimarchet@AdeleMyersPhD@hopfbifurcator🌟
🚨One of the coolest workshops in AI is back!
NeurReps 2025 is calling for papers on symmetry, geometry & topology in neural networks 🧠📐
If your work bridges theory & structure — don’t miss this.
📅 Deadline: Aug 22
We’re inspired + energized after three days of roundtable discussions, keynotes & lightning #tech talks about the challenges and future of imaging.
#ImagingTheFuture
🏆Geometric AI for weather forecasting is awarded TIME Invention of the year!🌎
Incredibly proud to serve as advisor for @atmo_ai - the leading startup in AI & Weather.
Congrats @johmathe@alevy@YvesMartinDT@hopfbifurcator & team!
*This* is AI for science 🌟
The Philippines just received the first live AI-based Weather Forecasting System in the region.
https://t.co/u9qCFl7Z5t
As extreme weather events become more frequent, AI weather forecasting system become critical parts of early warning systems (EWS).
Atmo is one of the TIME best inventions of 2024!
We are on a mission to make ultra-precise weather forecasting universally accessible. Atmo is honored to be recognized by TIME for our contribution.
See the full list here: https://t.co/hn1LDoMN7E
I am recruiting PhD students for 2025!😃
You want to reveal the geometric signatures of natural and artificial intelligence, and unlock the mysteries of the brain?🤖🧠
Apply to the UCSB Geometric Intelligence Lab✨
This is the view you'd have from... well, your desk🌴
https://t.co/rVWyLuPYm5
🚀I’m beyond excited to share that our paper has been accepted as a Spotlight at #NeurIPS2024! Super proud of the team’s great work! Once again, we make learning across neuroscience datasets easier!
✨ Recently accepted by #informationgeometry
Henrique K. Miyamoto @UnivParisSaclay, Fábio C. C. Meneghetti @IMECC_Unicamp, Julianna Pinele, Sueli I. R. Costa:
"On closed-form expressions for the Fisher–Rao distance"
Free view 🔗https://t.co/1q5OlmpnJt
https://t.co/RCZwQdqpmi